Discovery Early Career Researcher Award - Grant ID: DE230101116
Funder
Australian Research Council
Funding Amount
$420,000.00
Summary
Detecting Key Concepts from Low-Quality Data for Better Decision. The project aims to develop data analytics techniques that aid better decision making in high-stake scenarios when data are less-trustable. While data-aided decision making has been widely used, less-trustable data may significantly distort the decisions made and hurt people impacted by these decisions. The outcome of this project expects to be a series of techniques covering data understanding and enhancement, model development a ....Detecting Key Concepts from Low-Quality Data for Better Decision. The project aims to develop data analytics techniques that aid better decision making in high-stake scenarios when data are less-trustable. While data-aided decision making has been widely used, less-trustable data may significantly distort the decisions made and hurt people impacted by these decisions. The outcome of this project expects to be a series of techniques covering data understanding and enhancement, model development and fitting, and novelty detection, to reduce the damage of less-trustable data. The research expects to benefit the people and companies impacted by data-aided decision making in cybersecurity, healthcare and financial fraud detection, providing risk-control services.Read moreRead less
Cost-effective and Reliable Edge Caching for Software Vendors. This project aims to deliver a suite of models and techniques for cost-effective and reliable data caching in the multi-access edge computing (MEC) environment facilitated by 5G mobile network. MEC offers great promises for rapidly advancing mobile and IoT applications in various domains in Australia, e.g., smart cities, remote medical services, advanced manufacturing, etc. Combining graph analytics, optimisation techniques and game ....Cost-effective and Reliable Edge Caching for Software Vendors. This project aims to deliver a suite of models and techniques for cost-effective and reliable data caching in the multi-access edge computing (MEC) environment facilitated by 5G mobile network. MEC offers great promises for rapidly advancing mobile and IoT applications in various domains in Australia, e.g., smart cities, remote medical services, advanced manufacturing, etc. Combining graph analytics, optimisation techniques and game theory, this project tackles the new challenges in the placement, update and adaptation of edge data faced by software vendors embracing 5G. The outcomes can ease software vendors' cost and security concerns during the transition from 4G to 5G, and significantly promote the wave of 5G innovation in Australia.Read moreRead less